Possibilities of non-invasive post-genomics technologies in the prediction and early diagnosis of preeclampsia

Muminova K.T.

Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health of Russia, Moscow 117997, Ac. Oparina str. 4, Russia
Objective. To search and analyze the literature devoted to the study of possible markers and predictors of preeclampsia (PE), with the use of post-genomics technologies in particular.
Material and methods. Articles were searched in the database Pubmed. The review includes the data of foreign and Russian articles published in the past 15 years.
Results. The markers identified so far are shown to relate to early PE. The paper presents the results of post-genomics studies based on omics technologies. It shows the possibility of using the urine congophilia phenomenon as a new screening method.
Conclusion. It is necessary to conduct further investigations to develop a panel of non-invasive markers for PE in biological fluids, by using a proteomic and further urinary peptidome analysis as an example, which, reflecting the multifactorial pattern of PE, can simultaneously serve as both a predictor and a tool for monitoring the course of the disease, being a key component of personalized medicine.

Keywords

preeclampsia
biomarkers
predictors
proteome
peptidome
endogenous peptides
mass spectrometry
antiogenic factors
omics technologies
urinary proteomic and peptidome analyses
congophilia

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Received 09.06.2017

Accepted 23.06.2017

About the Authors

Muminova Kamilla Timurovna, junior researcher, 1st obstetrical department of pathology of pregnancy, Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health of Russia. 117997, Russia, Moscow, Ac. Oparina str. 4. E-mail: kamika91@mail.ru

For citations: Muminova K.T. Possibilities of non-invasive post-genomics technologies
in the prediction and early diagnosis of preeclampsia.
Akusherstvo i Ginekologiya/Obstetrics and Gynecology. 2018; (5): 5-10. (in Russian)
https://dx.doi.org/10.18565/aig.2018.5.5-10

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